Although the representations and processes underlying higher functions
in the brain are still largely unknown, the organization of sensory
cortices has been quite well understood for about 30 years. For example
in the visual system, the Nobel prize winning studies of Hubel and Wiesel
[20,22] showed that neurons in the
primary visual cortex are responsive to particular features in the
input, such as a line of a particular orientation at a particular
location in the visual field. The inputs in the retina to which a
neuron responds is called the receptive field of the neuron. All
neurons in a vertical column in the cortex typically have the same
receptive field and feature preferences. Vertical groups of neurons with
the same orientation preference are called orientation columns and
vertical groups with the same eye preference are called ocular dominance
columns. These feature preferences gradually vary across the surface of
the cortex in characteristic spatial patterns called cortical maps.

Often, altering the sensory environment of the young animal produces
readily observable changes in the organization of the afferent
connections to the cortex
[21,23,24]. Based on such
observations, it was generally believed that the response properties of
cortical cells are defined primarily by the organization of afferents.
Functionally for example the visual cortex was thought to be a collection of
filters for visual input, and the properties of the filters (such as
orientation preference) were thought to be defined by the patterns of
afferent synapses. Possible lateral interactions between cells across
the cortex were usually ignored, partly for simplicity, and partly
because there did not exist sufficient neurobiological data to form
well-defined theories about these interactions. Furthermore, based on
early discoveries on the plasticity of the cortex (such as those of
[1,4,5,24,46]),
it was believed that the cortical structure was influenced by the visual
environment only in early development, and that cortex was
essentially static afterwards. The lateral connections were thought to
play a secondary role in shaping visual cortex, with the primary role
attributed to plasticity of thalamocortical afferents.

Recently, however, a number of exciting results about
intracortical connectivity and dynamic processes in the cortex have
emerged. Lateral connections are found to be remarkably ordered: they
connect primarily areas with similar properties, such as neurons with
the same orientation or eye preference in the visual cortex
[13,15,28]. Such
organization is not genetically determined nor static, but develops
cooperatively and simultaneously with the thalamocortical afferents,
and changes dynamically according to visual experience throughout life
[6,7,8,26,28]).
The new understanding of cortical development and function thus differs
drastically from the old. Lateral interactions appear to play a much
larger role both in the development and function of the cortex than
previously believed, a role that we are only now beginning to
understand.

A crucial part of the effort to integrate lateral interactions into the
model of cortical function is computational modeling of the hypothesized
structures and processes. Studying complex, dynamic phenomena such as
those exhibited by the cortical circuits is usually very difficult
experimentally, but computational simulations may give insight into what
to look for. This book presents several such investigations, each
addressing the role of lateral interactions at a different level or from
a slightly different perspective. While a unified model of lateral
interactions in the cortex is yet to emerge, the book can give an
overview of the kinds of processes that may be going on, and thereby
further our understanding of information processing in the cortex.